Harvard Business School runs the “Launching Tech Ventures” class on the MBA course and I recently came across their reading list which I cross post here. IT’S THAT GOOD.

Unlike most MBA classes they don’t rely only on case studies and books but also utilize a ton of really great blog posts. I have read most of the articles and books over the last years below and can only recommend them – this is the best stuff out there!

Running Lean, by entrepreneur Ash Maurya, summarizes lean startup/customer development principles and does a great job of adapting Alex Osterwalder’s business model generation process to web startups. Maurya’s blog extends these ideas; he applies customer development processes to his current startup in this post, and discusses metrics in this one.

A step-by-step example from Aymeric Guarat-Apelli of “smoke testing,” i.e., assessing the viability of a new business concept by measuring consumer response to ads for a dummy site; Aymeric was inspired by this post by Tim Ferriss on how he used social media and A/B testing to build “Four Hour Workweek” into a best-seller.

Donald Reinertsen is a consultant and author of Principles of Product Development Flow. The book is dense and theoretical, but patient readers will learn a lot about the economic benefits of fast development cycles.

Startup metrics discussed in this MUST READ presentation by serial entrepreneur and angel investor Dave McClure, in which he describes his “AARRR” framework: acquisition, activation, retention, referral, revenue.

Inbound Marketing by HubSpot co-founders Brian Halligan and Dharmesh Shah offers advice on how to use Google, Facebook, Twitter, blogs, etc. to drive traffic to a website; presentation by Mike Volpe of HubSpot on this topic; HubSpots Marketing Hubs collect a wealth of resources and articles on online marketing.

A Stochastic Technologies’ historious blog post cautions A/B testers to get more data from their tests; the post cites an A/B test of identical pages that yielded, with 99.8% confidence, a 30% improvement for one of the pages after 1,000 visits and 3 days! After a few more days with more data, the improvement faded. Jason Cohen, founder of Smart Bear Software, explores the similar issues in this post.

B2B Selling

MUST READ Harvard Business Review article by Mark Leslie and Charles Holloway on the sales learning curve. Academics: note that Leslie, former founder/CEO of Veritas, has helped build a terrific case-based course on enterprise software sales management at Stanford Business School, STRAMGT 351.

More Books and Tools

Do More Faster, edited by Brad Feld and David Cohen, compiles advice across a range of topics from TechStars entrepreneurs and mentors.

Founders at Work, by Y Combinator’s Jessica Livingston, collects her interviews with two dozen founders relating their lessons learned.

Tom Hulme at IDEO has compiled and crowd-sourced a list of tools for tech startups, organized by function and company life cycle stage; a similar list compiled by Shyam Subramanyam; another list from Jaret Manuel; and my own list of free software tools for lean startups.

There is always a lot of buzz around innovative businesses on the web. Various investors and startups prefer different variations of models:

Incubators such as Rocket Internet prefer businesses where the customer need has been validated in the US and where they shift the geographic focus to Europe

Then there are business models which worked in an offline world and get shifted to the web as more and more consumers, time and ecomomic activity is on the web. Examples here are mobile payments, ecommerce or advertisements

Lastly there are businesses and innovations which are true, radical innovations such as a search engine or Bittorrent

A business in its entirety is more complex, though, and there is good literature on how to assess and decompose business models. Alexander Osterwalder’s Business Modell Generation for example is in one of the best recent books on this topic.

In a nutshell the book argues, that you can look at a business as a combination of the following components:

Approaches to creating a good value proposition

The difficult part is often the value proposition. From my experience, consumer businesses usually cater to at least one but usually a combination of the following use cases:

Discovery

Transaction

After Sales & Loyalty

Content

Sharing / Peer-to-Peer

Discovery

Discovery helps to find something. This is usually achieved in two ways:

Algorithmic search, where a ranking algorithm determines the relevancy of an object to the search. Google, Bing or Wolfram Alpha are good examples of business built on this

Curated search, here the content is hand selected by individuals. Early Yahoo was good example of curated search until the growth of web content outgrew the ability of Yahoo to curate. Other examples would be reddit or StumbleUpon

Transaction

Transaction means to exchange goods or services e.g. through e-Commerce stores or market places. Also I would put payment providers into this category. Examples are Amazon, Ebay or Paypal for the respective sub-segments

After Sales & Loyalty

Here the focus is to recommend further products, provide re-targeting ads for aborted shopping sessions and generally customer care.

Content

Written content is provided in the form of news sites and blogs. But are also use cases for (streaming) media, such as Spotify or Netflix and crowd sourcing content platforms such as Soundcloud or Youtube

Sharing / P2P

These are the traditional p2p file sharing networks started by Napster in the late 90s or Bittorrent. In my eyes more modern forms of this are social networks such as Facebook or Pinterest where you share status updates or other interesting things found on the web.

Final thoughts

Interestingly, when you look at most businesses they combine several of the use cases.

A P2P / sharing use case for example gets more interesting when you also have content and methods for discovery. Another example would be content which can be helped to provide information around products like the reviews of products on Amazon.

Most great startups that we admire really nailed one of these use cases and combine it with several other ones where they either partner with the best solution out there or achieve similar functionality to other sites without being extremely superior. The reason for this is that you simply can’t do everything in an excellent way. My favorite example for a failed attempt to do everything is when Apple tried to introduce Ping as a music social network as opposed to Spotify which clearly differentiated on superior content and chose to partner with the leading social network Facebook.

Some of the most interesting businesses such as Facebook, Twitter or Pinterest are based on communities. Obviously they are very attractive because they

create network effects which attract more users

have decreasing customer acquisition costs as the firm grows larger

are hard to copy because they are more than a combination of technical features

So far so easy.

But how do I get to this point? With frequency & surprises…

There is an important twist which make the most successful services so sticky and addicting. Interaction is

a) frequent
b) outcome is unclear

The frequency of interaction helps to ideally become a habit like checking emails or Facebook. The very best companies even become a verb. Think about statements like “I’ll google that later” or “Let’s skype”.

Interestingly, the underlying requirement is that the outcome of using the service is unclear. Consumers want to be surprised and discover something cool, fun or useful. Take pictures from a friends vacation for example, or a cool party that is planned for the weekend. Basically anything qualifies which is relevant to the user but what the user couldn’t predict before he opened the service and used it.

Another good example which illustrates this point is an Excel spreadsheet with your business plan. The outcome is clear (i.e. the calculations haven’t changed) vs the stock market or online news page where the outcome of opening the website is not clear. Which one do you check more often?

So what do we learn from this?

Lesson 1: Unexpected content must be relevant and to be that it must be within certain parameters. With Facebook you would expect an update from your friends vs. Linkedin where you would rather expect some information regarding your business contacts.

Lesson 2: This drives frequent visits and increases the likeliness that the service becomes a habit.

Lesson 3: The parameters need to be established over time and can’t be all planned upfront. The community needs to agree on a set of rules. The biggest danger here is that the community grows too fast in the early days and is not homogenous enough to really build out a core group which adheres to these rules. Or in Crossing the Chasm terms: with communities the early majority needs the guidance by the early adopters. The chasm still exists because the early majority are also pragmatists. For them the service or product is the combination of technical features and the community that already uses it.

Negotiating contracts in the music industry is hard. Spotify was founded 2006 and only managed to enter the US market in 2011. It’s still lacking licenses for Germany, Italy or Canada to name just a few. As a result, a major business activity for Spotify is to negotiate and manage contracts. Once these have been established they act as a market entry barrier for innovative new music services.

These contracts have also major impact on the economics of the business model. Costs for content and delivery rise as user numbers keep growing. As a result it’s pretty hard to earn healthy profits as pure streaming provider, despite that some artists complain about low royalty payments. Obviously, Spotify is currently also doing major investments in product development which impact profitability on the short term but this is to be expected from a startup. However, the long term implications of record labels as gatekeepers to content, their reluctance to innovate, and the ability to squeeze margins for streaming providers as well as artists are a major concern.

Spotify’s recent announcement that it’s turning its service into a platform is great news: It reduces the difficulty to experiment with innovative concepts and enables a whole new level of innovation fueled by the creativity and drive of a developer community. Besides karma points, Spotify is benefitting by the ability to offer more functionality and use cases which cater to specific audiences on its platform.
In terms of profits this is great, too: Similar to Facebook and the social graph, Spotify provides a service to app developers by making music content legally and easily accessible. For this it can charge a fee and tap new revenue streams.

There’s only one thing which I just don’t get, though: Enabling legal access to a music catalog and charging fees for that is the core business model of a record label. Why did record labels wait for Spotify to get this done?!?

Twitter is an awesome service. It’s one my regular sites which I always login to as soon as I start a browser. But I have doubts that it will be in its current form a mass communication tool such as Email.

I think Twitter has three main use cases:

a) For broadcasting: because you don’t have to mutually agree on friendship the resulting graph is more similar to the media industry where it is possible to publicize a news and opinions in a one to many approach
b) For trends/analytics: if you really want to know what people are thinking about your product create a Twitter search. You will find out quickly what’s wrong and can engage directly with you customers
c) Hand curated discovery: Yahoo ultimately declined in search because the web grew faster than Yahoo’s ability to hand curate search results. Twitter kind of brings that back in a crowed sourced way. They’re taking it from a slightly different angle because you d on’t have to search, the information “finds” you. Of course you can manually maintain an RSS feed use TechMeme, StumpleUpon or good old browser bookmarks, but Twitter allows to filter news by the interests of the people who you follow. As a consequence it is also able deal with news which is normally not in one’s core interest areas would pretty quickly come through if it’s important enough like a natural disaster.

Why media and tech love Twitter

Many argue about how similar or different Twitter is to Facebook by pointing out the use cases implied by the underlying 1 to many graph. Few doubt that Twitter will become a universally used service (in the way that email, Facebook or Amazon are used).

I am not so sure to be honest. I see why the media, tech enthusiasts and Venture Capitalists love Twitter. Most Top 20 users on Twitter are from the media industry or politics.

And the tech community is always hunting for the next big trend, so for them it is a fantastic long tail analytics and curation tool (as well as a very promising investment opportunity). See here or here.

In my eyes Twitter faces a classic crossing the chasm problem. Twitter has successfully scaled through the innovators and early adopters, but the majority are pragmatists. If I look at the use cases above and at the non-tech group of family and friends, I don’t see that they find the same things equally appealing.

This group values opinions and updates by friends and the ability of instant delivery of messages and that’s why Email and Facebook are tools appealing to huge masses. These friends may read some journals which provide job related information and get general news from the big news sites on the web or TV. In my understanding this satisfies their need for information. They don’t have a “customer problem” in terms of that they don’t get enough news.

So what could Twitter do?

voting up/down for posts to improve the signal/noise ratio?

allowing more than 140chars so it doesn’t feel like a 1990 style mobile text anymore? You don’t need to go for the other extreme, but how about 50 words?

the above would require a more powerful and easier to use tagging system to foster better categorization?

use an app store approach to centralize all twitter add ons and make them easily accessible for main stream audiences?

Unfortunately, I think it would involve adding features (it’s pretty hard to remove anything – that’s for sure) and I am sure that this has been intensely discussed internally. However, I have never heard of an innovative market leader who stayed in that spot by moving nowhere.